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Target Localization Using MIMO-Monopulse: Application on 79 GHz FMCW Automotive Radar

机译:使用MIMO Monopulse的目标本地化:在79 GHz FMCW汽车雷达上的应用

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摘要

Automotive radar is widely used for driving safety support and it is a key element of future autonomous vehicles. Radar sensors have the property that the performance is not to be affected by low vision conditions compared with camera sensors or laser based radar sensors, which makes it crucial for the autonomous driving system.Automotive radar system utilizes millimeter-wave band to detect the range, velocity and direction of arrival (DOA). Commercial 24 GHz and 77GHz radar have been well developed in vehicle applications at present, and the future trend is 79 GHz solution with wider 4 GHz bandwidth, which has been defined by the European Commission in 2004 as the frequency allocation for automotive shortrange radar systems. The main modulation method of automotive radar is Frequency-Modulated Continous-Wave(FMCW), which holds advantages including high-resolution distance measurement, quick updating and lower sampling frequency required on hardware.%good functions in the various weather condition.The resolution and accuracy of DOA estimation depend on the number of used antennas and their physical size. To improve the performance advanced algorithms and antenna configurations can be used. So-called super-resolution techniques can improve the estimation performance but suffer when few measurements are available and the number of targets is unknown, and the performance will also be degraded by correlated signals.Monopulse is an established technique for radars for precision angle estimation. It enables DOA realized in only one pulse and requires quite less computation complexity. Conventional monopulse with one transmitter and two receivers and phased array monopulse have been well developed especially in tracking radar system. MIMO-monopulse has been studied in some literature, but most of them utilize distributed MIMO. The research and application of colocated MIMO-monopulse are still in progress. In FMCW automotive radar application, clutter may have a strong effect on DOA detection and estimation of targets with low RCS, e.g. pedestrian. With Space-Time Adaptive Processing(STAP), it is possible to suppress the clutter in the angle-Doppler domain. MIMO-monopulse basically utilizes digital beamformer to generate sum and difference channel, which also allows STAP processing to obtain adaptive sum and difference weighting. With STAP clutter can be canceled, thus false detection of MIMO-monopulse will be avoided. In this master thesis, we propose the solution of angle estimation algorithm using MIMO-monopulse based on an actual automotive radar provided by NXP using colocated MIMO antenna. The algorithm is simulated through Matlab and verified on real experimental data. The performance of the algorithm is compared with conventional DOA algorithm and the advantages and disadvantages are analyzed. A feasible extension to STAP will be discussed to suppress the clutter for preventing false DOA estimation.Since monopulse estimator has been approved high performance in the field of single target tracking (such as low RCS pedestrian), our proposed algorithm is also validated in single and multiple target DOA estimations, which is an attractive scenario for a potential application using MIMO-monopulse.
机译:汽车雷达广泛应用于驾驶安全的支持,这是未来的自动驾驶汽车的一个关键因素。雷达传感器具有这样的性质的性能不被通过低视力情况与相机传感器或基于激光雷达传感器相比的影响,这使得它至关重要的自主驱动system.Automotive雷达系统利用毫米波频段,以检测的范围内,速度和到达(DOA)的方向。商业24 GHz和用于77GHz雷达已经在目前车辆的应用得到了很好的发展,未来的趋势是更广泛的4 GHz的带宽,已经由欧盟委员会于2004年定义为汽车短程雷达系统的频率分配79 GHz的解决方案。汽车雷达的主要调制方法是频率调制连续型波(FMCW),其保持的优点,包括高清晰度测距,快速更新和较低的采样在不同的天气condition.The分辨率上的硬件。%的良好功能所需的频率和DOA估计的精度取决于所使用的天线的数量和它们的物理尺寸。为提高性能先进的算法,可用于天线配置。所谓的超分辨率技术可以提高估计性能,但在几次测量可用,目标数量是未知的遭遇,而且性能也将受到相关signals.Monopulse降解是雷达精密角度估计的成熟技术。它使DOA实现只在一个脉冲,并需要相当少的计算复杂度。与一个发射器和两个接收器和相控阵单脉冲单脉冲常规已尤其是在跟踪雷达系统得到很好的开发。 MIMO-单脉冲已经研究了一些文献,但大多采用分布式MIMO。该研究共址MIMO-单脉冲的应用程序仍在进行中。在FMCW汽车雷达应用,杂波可能对DOA检测和具有低RCS目标估计有很强的影响,例如行人。空时自适应处理(STAP),可以抑制角度 - 多普勒域的混乱。 MIMO-单脉冲基本上采用数字波束成形器,以产生和,差信道,其也允许STAP处理,以获得自适应和与差的权重。与STAP杂波可以取消,MIMO-单脉冲的从而错误检测将被避免。在该硕士论文中,我们使用基于由NXP提供一个实际的汽车雷达MIMO-单脉冲使用同一位置MIMO天线提出角估计算法的解决方案。该算法通过Matlab的仿真和真实的实验数据验证。该算法的性能与常规DOA算法相比和优点和缺点进行了分析。一个可行的扩展STAP将讨论压制,防止误DOA estimation.Since杂波单脉冲估计已经被批准在单目标跟踪(如低RCS行人)领域的高性能,我们提出的算法也验证了单,多个目标DOA估计,这是用于使用MIMO-单脉冲具有潜在的应用有吸引力的方案。

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